Workload aware data partitioning
2022, May, Norman, Boehm, Alexander, Moerkotte, Guido, Brendle, Michael, Valiyev, Mahammad, Weber, Nick, Schulze, Robert, Grossniklaus, Michael
Techniques and solutions are described for partitioning data among different types of computer-readable storage media, such as between RAM and disk-based storage. A measured workload can be used to estimate data access for one or more possible partition arrangements. The partitions arrangements can be automatically enumerated. Scores for the partition arrangements can be calculated, where a score can indicate how efficiently a partition arrangement places frequently accessed data into storage specified for frequently-accessed data and placed infrequently accessed data into storage specified for infrequently accessed data.
Context-Aware Data Management : An Object-Oriented Version Model
2012, Grossniklaus, Michael
Revision with unchanged content. Context-awareness is a requirement of many modern applications. While several solutions exist to gather, represent and process context, very few provide management of context-aware data. In this book, a two-dimensional version model is presented, that allows managing context-dependent variants, while, at the same time, keeping track of the revision history. Queries are processed based on a matching algorithm that uses the current context of the system to select the best object. As an application of this extended database, a content management system has been designed and implemented. This Extensible Content Management System (XCM) provides a flexible platform for web engineering, built on the separation of content, structure, view and presentation. Metadata about these concepts is managed within the extended database and therefore all aspects of a web system become context-aware. Using XCM, a mobile tourist information system (EdFest) was developed. EdFest offers multi-channel interaction through standard web channels and a novel paper-based channel. This book is targeted at developers and researchers in mobile, ubiquitous and pervasive computing as well as in web engineering.
Web Engineering : 9th International Conference, ICWE 2009 San Sebastián, Spain, June 24-26 2009 ; Proceedings
2009, Gaedke, Martin, Grossniklaus, Michael, Díaz, Oscar
This book constitutes the refereed proceedings of the 9th International Conference on Web Engineering, ICWE 2009, held in San Sebastian, Spain in June 2009. The 22 revised full papers and 15 revised short papers presented together with 8 posters and 10 demonstration papers were carefully reviewed and selected from 90 submissions. The papers are organized in topical sections on accessibility and usability, component-based web engineering: portals and mashups, data and semantics, model-driven web engineering, navigation, process, planning and phases, quality, rich internet applications, search, testing, web services, SOA and REST, and web 2.0.
Towards Reproducible Research of Event Detection Techniques for Twitter
2019-06, Weiler, Andreas, Schilling, Harry, Kircher, Lukas, Grossniklaus, Michael
A major challenge in many research areas is reproducibility of implementations, experiments, or evaluations. New data sources and research directions complicate the reproducibility even more. For example, Twitter continues to gain popularity as a source of up-to-date news and information. As a result, numerous event detection techniques have been proposed to cope with the steadily increasing rate and volume of social media data streams. Although some of these works provide their implementation or conduct an evaluation of the proposed technique, it is almost impossible to reproduce their experiments. The main drawback is that Twitter prohibits the release of crawled datasets that are used by researchers in their experiments. In this work, we present a survey of the vast landscape of implementations, experiments, and evaluations presented by the different research works. Furthermore, we propose a reproducibility toolkit including Twistor (Twitter Stream Simulator), which can be used to simulate an artificial Twitter data stream (including events) as input for the experiments or evaluations of event detection techniques. We further present the experimental application of the reproducibility toolkit to state-of-the-art event detection techniques.